108 citations · 587 across the 36 of their papers we have counts for
4 papers · 1 filter
Confidence Estimation via Auxiliary Models
Charles Corbière, Nicolas Thome, Antoine Saporta +3
Reliably quantifying the confidence of deep neural classifiers is a challenging yet fundamental requirement for deploying such models in safety-critical applications. In this paper…
Probabilistic Time Series Forecasting with Structured Shape and Temporal Diversity
Vincent Le Guen, Nicolas Thome
Probabilistic forecasting consists in predicting a distribution of possible future outcomes. In this paper, we address this problem for non-stationary time series, which is very ch…
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
Yuan Yin, Vincent Le Guen, Jérémie Dona +4
Forecasting complex dynamical phenomena in settings where only partial knowledge of their dynamics is available is a prevalent problem across various scientific fields. While purel…
Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction
Vincent Le Guen, Nicolas Thome
Leveraging physical knowledge described by partial differential equations (PDEs) is an appealing way to improve unsupervised video prediction methods. Since physics is too restrict…